In higher eukaryotes such as humans, genes are transcribed to pre-mRNAs, in which exons (RNA segments that code for proteins) are separated from each other by intervening introns (RNA segments that do not code for proteins). A gene may generate different mature mRNA transcripts by selectively including different combinations of exons. This biological process is referred to as alternative splicing and is the main strategy for genes to generate proteomic diversity. Extenstive evidences indicate that over 95% of human genes undergo alternative splicing. Aberrant splicing of pre-mRNAs can cause various human diseases, such as cancers, aging related diseases, heart diseases and neuro-development diseases. Recent studies have shown that small non-coding RNAs play an essential regulatory role in alternative splicing. For example, small interfering RNAs (siRNAs) can regulate alternative splicing by modulating chromatin structure. The overarching goal of this project is to develop a set of novel statistical tools to advance our knowledge of the regulatory role of small RNAs on alternative splicing. More specifically, the invetigators of this project will (1) develop effective significance testing theory and methods via generalized smoothing spline ANOVA models to identify genome-wide small RNA targets; (2) develop a new statistical framework for isoform assembly and quantification via joint modeling multisample RNA-seq data; (3) bridge the research gap in the study of small RNAs by elucidating the regulatory role of small RNAs on isoform expression. Although the proposed methods are developed to address the current analytical challenges in isoform and small RNA analysis, a burgeoning area in biology studies, the statistical theory and methods can be broadly applied to many research fields.